Chemical Processing - October 2007 - (Page 34)

the operator (per the written procedures) contacted the plant manager, who gave approval to proceed with the shutdown. This caused a production outage that impacted delivery of a critical intermediate to one of the company’s key customers. Further, the sequence of events and the elapsed time from initial warnings to shutdown resulted in extreme temperatures within the turbine. This led to significant damage, necessitating the replacement of its main bearings. The root cause turned out to be that back-up pump had not come online as expected. In doing the situation analysis, the company discovered a number of specific issues: 1. The back-up pump wasn’t instrumented in the same manner as the primary one, so there wasn’t any critical warning to the operator. 2. Condition information for the primary pump and the back-up pump weren’t linked. 3. The pump, temperature/pressure and turbine data weren’t connected. Each was handled discretely by the operator in separate areas of the human/machine interface (HMI); the combined elapsed time in dealing with the discrete events exceeded the safe shutdown point for the turbine. 4. No automated communication alerted maintenance, engineering or plant management to the developing issue. 5. The operator didn’t have any way of seeing the maintenance status of the primary assets including the pumps — this would have shown that the back-up pump had a pending inspection because of previously reported issues. Looking at this real-life example in its entirety, no particular action or practice alone could be blamed. Instead, the situation arose because of the lack of context and ineffective use (i.e., management) of available information. The foundation for success As the example underlines, effective condition manage- ment must address all of the elements together. Specifically this means: • collecting the right data (condition, process area and system); • gathering the complete set of data necessary to provide the context needed to accurately assess an issue and its impact; • automating the response, including actions and escalations; and • enforcing the post-event analysis and continuous improvement process. Moving to condition management is ultimately a knowledge management challenge. In many companies, such a move requires a change in both technical and business process practices. This challenge is manageable but firms need to be committed to the change in approach and need the discipline to effectively implement and sustain it. The process has to include the use of supporting tools and technologies that allow the capture of the institutional knowledge currently existing in plant personnel across all the disciplines. Condition management fundamentally is a closed-loop model with four main elements — collect, analyze, act and optimize. This model provides the framework for translating the business needs into a solution architecture for a plant. Figure 1 shows the relationships among these elements, starting at the process measurement level through decision support and feeding back to the process. Getting started As with any change process, it’s critical to understand the starting point. This demands taking a hard look at several areas and asking some tough questions: Culture. Does the company understand that there are issues and that there’s inherent and significant value in resolving them? As a simple test, can people articulate the impact or cost of an unplanned outage? Is the company really willing and ready to change? Effective condition management will include changes to business processes and roles, so these points are fundamental. Business processes. Are the firm’s processes documented? Have they recently been validated or benchmarked against others in the industry and best practices? In many cases, simple process enhancements or better communication can deliver significant performance improvements. Don’t apply technology without this process baseline. Note in particular that a formal approach based on root-cause analysis and including continuous improvement efforts is a fundamental requirement. At a broader level check whether a formal lifecycle management program is in place. A recent survey conducted by the ARC Advisory Group found that companies that had adopted such a program had a significantly better return on assets than those that hadn’t. The research also indicated that www.chemicalprocessing.com >> ARC collaborative asset lifecycle model Figure 2. In CALM, the operate/maintain stage offers the largest portion of return-onasset improvement. Source: ARC. 34 • October 2007 http://www.chemicalprocessing.com

Table of Contents Feed for the Digital Edition of Chemical Processing - October 2007

Chemical Processing - October 2007 Contents From the Editor ChemicalProcessing.com Field Notes In Process Energy Saver Compliance Advisor Biofeedstocks See Real Growth Become a Cyber-Security Pacesetter Go Beyond Condition Monitoring Disposable Equipment Earns Lasting Role Improve Control Loop Performance Ethanol Plant Boosts Output and Saves Energy Process Puzzler Plant InSites Equipment & Services Ad Lits Product Spotlight/Classifieds Ad Index End Point

Chemical Processing - October 2007

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